Search NASA⌕ Search

SEARCH · Search NASA

Results for “Monte Carlo Code”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Advanced instrumentation and analysis methods for in-pile thermal and nuclear measurements: from out-of-pile studies to irradiation campaigns

Research and development on nuclear fuel behavior under irradiations and accelerated ageing of structure materials is a key issue for sustainable nuclear energy in order to meet specific needs by keeping the best level of safety. A new Material Testing Reactor (MTR), the Jules Horowitz Reactor (JHR) currently under construction in the South of France in the CEA Cadarache research centre will offer a real opportunity to perform R and D programs and hence will crucially contribute to the selection, optimization and qualification of innovative materials and fuels. To perform such programs advanced accurate and innovative experiments, irradiation devices that contain material and fuel samples are required to be set up inside or beside the reactor core. These experiments needs beforehand in situ and on line sophisticated measurements to accurately reach specific and determining parameters such as thermal and fast neutron fluxes, nuclear heating and temperature conditions to precisely monitor and control the conducted assays. Consequently, since 2009 CEA and Aix-Marseille University collaborate in order to design and develop a new multi-sensor device which will be dedicated to measuring profiles of such conditions inside the experimental channels of the JHR. These works are performed in the framework of two complementary joint research programs called MAHRI-BETHY and INCORE. These programs couple experimental studies carried out both out-of nuclear fluxes (in laboratory) and under irradiation conditions (in OSIRIS MTR reactor in France and MARIA MTR reactor in Poland) with numerical works realized by thermal simulations (CAST3M code) and Monte Carlo simulations (MCNP code). These programs deal with three main aims. The first one corresponds to the design and/or the test of new in-pile instrumentation. The second one concerns the development of advanced calibration procedures in particular in the case of one specific sensor: a differential calorimeter used to quantify nuclear heating. The last one consists in the development of accurate measurement and analysis methods. The paper will be dedicated to a complete review of the experimental and numerical works performed since 2009 thanks to two parts. The first part will detail a new thermal approach implemented to improve nuclear heating measurements by radiometric calorimeters. New experimental tools (calorimeter prototypes and set-ups such BETHY Bench) developed to perform preliminary out-of-pile studies under suitable conditions will be presented (temperature and velocity of the external cooling fluid, heat source localization and intensity inside the calorimetric cells). Then the response of two kinds of sensors, their calibrations curves and their thermal behaviors will be compared for various parameters. Finally validated numerical thermal and Monte Carlo works will be discussed to propose new improvements. The second parts of the paper will focus on works realized in order to design, develop and test the first prototype of the multi-sensor device called CARMEN [7-9]. The two mock-ups dedicated respectively to neutron measurements and photon measurements will be detailed. The results obtained during two irradiation campaigns inside the periphery of OSIRIS reactor will be shown. The new analysis method will be discussed. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Depletion capabilities in the OpenMC Monte Carlo particle transport code

A depletion solver has been implemented in OpenMC and is described herein. The depletion solver is implemented in Python and interfaces with OpenMC’s transport solver through a C++ application programming interface, which enables an in-memory transport-depletion coupling. Multiple integration methods for advancing in time have been implemented and exhibit tradeoffs in cost, accuracy, and memory use. For all time integration methods, evaluation of the matrix exponential is performed by using the incomplete partial fraction form of the Chebyshev rational approximation method. Simulations of a pressurized water reactor (PWR) pincell and a sodium-cooled fast reactor (SFR) assembly were carried out with OpenMC and Serpent. For both problems, the use of a high-fidelity depletion chain results in predictions of k eff that agree within 20–30 pcm between OpenMC and Serpent. Predicted actinide concentrations were found to agree to a fraction of a percent, and most fission product concentrations were found to agree within 1%. Here, the few cases where larger differences were observed can be attributed either to differences in how the energy dependence of fission product yields is handled or deficiencies in the nuclear data used. OpenMC simulations of the PWR and SFR problems using a simplified 228-nuclide depletion chain demonstrate that it achieves accuracy close to that of the full, high-fidelity depletion chain with respect to the studied responses.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

$κ$monty: a Monte Carlo Compton scattering code including non-thermal electrons

Low-luminosity active galactic nuclei are strong sources of X-ray emission produced by Compton scattering originating from the accretion flows surrounding their supermassive black holes. The shape and energy of the resulting spectrum depend on the shape of the underlying electron distribution function (DF). In this work, we present an extended version of the GRMONTY code, called ΚMONTY. The GRMONTY code previously only included a thermal Maxwell–Jütner electron DF. We extend the GRMONTY code with non-thermal electron DFs, namely the κ and power-law DFs, implement Cartesian Kerr–Schild coordinates, accelerate the code with MPI, and couple the code to the non-uniform adaptive mesh refinement grid data from the general relativistic magnetohydrodynamics code BHAC. For the Compton scattering process, we derive two sampling kernels for both DFs. Finally, we present a series of code tests to verify the accuracy of our schemes. The implementation of non-thermal DFs opens the possibility of studying the effect of non-thermal emission on previously developed black hole accretion models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Initial Neutronics and Thermal-Hydraulic Coupling for Spent Nuclear Fuel Canister

This report documents work performed supporting the US Department of Energy (DOE) Nuclear Energy Spent Fuel and Waste Disposition, Spent Fuel and Waste Science and Technology, under work breakdown structure element 1.08.01.03.05, “Direct Disposal of Dual Purpose Canisters.” In particular, this appendix fulfills the M3 milestone, M3SF-19OR010305015, “Multiphysics criticality consequence analysis capability development status report,” as Revision 1 to M3SF-19OR010305016, “Initial neutronic and thermal hydraulic coupling for waste package” within work package SF-19OR01030501, “Direct Disposal of Dual Purpose Canisters–ORNL.” This report presents the initial development status of a multiphysics criticality consequence simulation framework, Terrenus. Terrenus currently couples two physics codes: the Monte Carlo radiation transport code Shift and the thermal-hydraulics code COBRA-SFS. The coupling capability has been demonstrated using a simplified 3 x 3 fuel pin lattice. Terrenus will be developed further to include (1) general geometry package support, allowing modeling of a spent nuclear fuel (SNF) cask with all structural details, (2) a depletion solver to determine the change in nuclide composition at the end of each time step, and (3) a mechanics code to determine any structural impact due to a criticality event. Future research and development works include identifying/developing a modern two-phase thermal-hydraulics code and developing an approach to solve fast neutronic transients. The goal of this multiphysics framework is to determine the feasibility of direct disposal of currently loaded SNF canisters by including or excluding a criticality event from a repository performance analysis framework in terms of consequences. The revision 1 to this report includes extending Terrenus to a 17 x 17 pressurized water reactor (PWR) fuel assembly. We also investigated the phenomena necessary to quench a critical reaction, and investigated the water level necessary to achieve criticality in a typical canister. Finally, we describe the initial implementation of a critical power search capability.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Constrained Bayesian Optimization of Criticality Experiments [Slides]

The design of criticality experiments is typically an iterative process that employs a Monte Carlo transport code. The goal is to find a design that optimizes some variable, like the sensitivity of a response to a cross section, while simultaneously ensuring criticality. The high fidelity of the Monte Carlo code is a great asset, but it makes exploring the design space computationally expensive. Herein, we present how a constrained Bayesian optimization algorithm can be used to efficiently design a criticality experiment. It uses Gaussian processes as a surrogate model to probe the design space and to reduce the number of code executions that are needed to find the optimum. We demonstrate constrained Bayesian optimization with a Pu-239/polyethylene solution system and a TEX experiment that is designed for criticality safety validation of a nuclear waste model at the Hanford Site. For both systems, a global optimum was found within 75 Monte Carlo simulations.

42 ENGINEERING↗
DOE OSTI2020

Constrained Bayesian optimization of criticality experiments

The design of criticality experiments is typically an iterative process that employs a Monte Carlo transport code. The goal is to find a design that optimizes some variable, like the sensitivity of a response to a cross section, while simultaneously ensuring criticality. The high fidelity of the Monte Carlo code is a great asset, but it makes exploring the design space computationally expensive. Herein, we present how a constrained Bayesian optimization algorithm can be used to efficiently design a criticality experiment. It uses Gaussian processes as a surrogate model to probe the design space and to reduce the number of code executions that are needed to find the optimum. Furthermore, we demonstrate constrained Bayesian optimization with a Pu-239/polyethylene solution system and a TEX experiment that is designed for criticality safety validation of a nuclear waste model at the Hanford Site. For both systems, a global optimum was found within 75 Monte Carlo simulations.

42 ENGINEERING↗
DOE OSTI2020

Constrained Bayesian Optimization of Criticality Experiments at LLNL [Slides]

The design of criticality experiments is typically an iterative process that employs a Monte Carlo transport code. The goal is to find a design that optimizes some variable, like the sensitivity of a response to a cross section, while simultaneously ensuring criticality. The high fidelity of the Monte Carlo code is a great asset, but it makes exploring the design space computationally expensive. Herein, we present how a constrained Bayesian optimization algorithm can be used to efficiently design a criticality experiment. It uses Gaussian processes as a surrogate model to probe the design space and to reduce the number of code executions that are needed to find the optimum. We demonstrate constrained Bayesian optimization with a Pu-239/polyethylene solution system and a TEX experiment that is designed for critical ity safety validation of a nuclear waste model at the Hanford Site. For both systems, a global optimum was found within 75 Monte Carlo simulations.

42 ENGINEERING↗
DOE OSTI2017

Semi-Analytical Benchmarks for MCNP6

Code verification is an extremely important process that involves proving or disproving the validity of code algorithms by comparing them against analytical results of the underlying physics or mathematical theory on which the code is based upon. Monte Carlo transport codes such as MCNP6 undergo verification and testing upon every release to ensure that the codes are properly simulating nature. Specifically, MCNP6 has multiple sets of problems with known analytic solutions that are used for code verification. Most of the verification problems are fairly simple due to the fact that they are usually composed of few materials, with simplified cross-sections, or physics approximations, and simple geometry. These approximations make the transport equation possible to solve analytically or semi-analytically, and thus they are quite valuable in verifying that the code algorithms and methods (Monte Carlo, discrete ordinates, etc.) are operating as intended. The remainder of this paper is organized as follows: first we briefly discuss the theory behind the benchmarks problems, then the numerical results are presented, and finally we conclude with general remarks on this and possible future work.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Calculating Control Rod Differential Worth Using Adjoint-Weighted Method

Recently, there are more and more research on using Monte Carlo method to calculate reactor important parameters. Control rod worth is one of the important parameters as it can determine the critical control rod position. There are two presentations of the control rod worth for utilization purpose, integral and differential. The former is the total reactivity change, while the latter is the reactivity change caused by per unit movement. In Monte Carlo calculation, differential control rod worth of a particular position is estimated by finite difference of reactivity between a small gap divided by gap distance. Though easy to implemented, the problem of this approach lies in that too large gap will enlarge error between 'differential' and 'difference', while too small gap will be disturbed by error caused by random fluctuation. Monte Carlo perturbation theory has been used to calculate the k{sub eff} sensitivity to certain parameters for a long time. By calculating the differential coefficient along with the k{sub eff}, this method is quite time-consuming and relatively accurate compared to finite difference method. Nevertheless, most of perturbation research focus on the perturbation of nuclide density or nuclear data. For geometrical perturbation, limited research was done before. Takahashi estimated the k{sub eff} sensitivity to reflector movement of pulsed fast reactor. MCNP6 used adjoint-weighted method for Godiva, Zeus and uranium oxyfluoride solution container benchmarks. This paper tries to apply the perturbation method to the determination of control rod differential worth. In this paper, based on RMC, a continuous-energy Reactor Monte Carlo transport code, Iterated Fission Probability method (IFP) is researched to calculate control rod differential worth on assembly level. IFP was originally developed by Hurwitz, and has been adopted by most of Monte Carlo code to compute adjoint-weighted parameters. This paper is organized with four parts. The first is introduction. Adjoint-weighted method is introduced in the second part. Problem 4 of benchmark from CASL is built to verify the method. Conclusion is given in final part.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Computational Modeling and Simulation for Nonproliferation: The History (and Present) of Monte Carlo and the MCNP(R) Code at Los Alamos [Slides]

The emergence of the Monte Carlo method as a research tool springs from work done at Los Alamos in the 1940s.Monte Carlo and the MCNP Code have been and continue to be developed at Los Alamos for many decades. From basic science in support of understanding nuclear interaction physics to global security applications, application uses of the code are extensive. Recent R&D projects and code modernization efforts make the MCNP code a great tool for nuclear nonproliferation applications. In collaboration with nuclear safeguards experts, new training has just recently been developed to help new practitioners learn how to use the code for nuclear safeguards applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

MODEX ─ A Program for Calculation of the Energy Spectra of Particle Emitted in the Reactions of Pre-Equilibrium and Equilibrium Statistical Decays

The program is described intended for calculation of the energy distribution of particles, emitted by excited nucleus, using the Modified Exciton Model (MEM). The complete text of the program is presented in FORTRAN66 language. We reproduce here this 1974 JINR Communication as it was never published in a journal but it represents a historical interest as the first (in the world) Monte Carlo realization of the preequilibrium plus evaporation model, and was and still is used in dozens of countries all over the world. E.g., the current CEM03.03 and LAQGSM03.03 event-generators of the latest LANL Monte Carlo transport code MCNP6 have today modified parts from MODEX, the first Monte Carlo preequilibrium code in the world. [Abstract is in English. The 1974 JINR Communication is in Russian.]

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

SU-F-T-376: The Efficiency of Calculating Photonuclear Reaction On High-Energy Photon Therapy by Monte Carlo Method

Purpose: Secondary-neutrons having harmful influences to a human body are generated by photonuclear reaction on high-energy photon therapy. Their characteristics are not known in detail since the calculation to evaluate them takes very long time. PHITS(Particle and Heavy Ion Transport code System) Monte Carlo code since versions 2.80 has the new parameter “pnimul” raising the probability of occurring photonuclear reaction forcibly to make the efficiency of calculation. We investigated the optimum value of “pnimul” on high-energy photon therapy. Methods: The geometry of accelerator head based on the specification of a Varian Clinac 21EX was used for PHITS ver. 2.80. The phantom (30 cm * 30 cm * 30 cm) filled the composition defined by ICRU(International Commission on Radiation Units) was placed at source-surface distance 100 cm. We calculated the neutron energy spectra in the surface of ICRU phantom with “pnimal” setting 1, 10, 100, 1000, 10000 and compared the total calculation time and the behavior of photon using PDD(Percentage Depth Dose) and OCR(Off-Center Ratio). Next, the cutoff energy of photon, electron and positron were investigated for the calculation efficiency with 4, 5, 6 and 7 MeV. Results: The calculation total time until the errors of neutron fluence become within 1% decreased as increasing “pnimul”. PDD and OCR showed no differences by the parameter. The calculation time setting the cutoff energy like 4, 5, 6 and 7 MeV decreased as increasing the cutoff energy. However, the errors of photon become within 1% did not decrease by the cutoff energy. Conclusion: The optimum values of “pnimul” and the cutoff energy were investigated on high-energy photon therapy. It is suggest that using the optimum “pnimul” makes the calculation efficiency. The study of the cutoff energy need more investigation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Monte Carlo Techniques for Nuclear Systems - Theory Lectures

These are lecture notes for a Monte Carlo class given at the University of New Mexico. The following topics are covered: course information; nuclear eng. review & MC; random numbers and sampling; computational geometry; collision physics; tallies and statistics; eigenvalue calculations I; eigenvalue calculations II; eigenvalue calculations III; variance reduction; parallel Monte Carlo; parameter studies; fission matrix and higher eigenmodes; doppler broadening; Monte Carlo depletion; HTGR modeling; coupled MC and T/H calculations; fission energy deposition. Solving particle transport problems with the Monte Carlo method is simple - just simulate the particle behavior. The devil is in the details, however. These lectures provide a balanced approach to the theory and practice of Monte Carlo simulation codes. The first lectures provide an overview of Monte Carlo simulation methods, covering the transport equation, random sampling, computational geometry, collision physics, and statistics. The next lectures focus on the state-of-the-art in Monte Carlo criticality simulations, covering the theory of eigenvalue calculations, convergence analysis, dominance ratio calculations, bias in Keff and tallies, bias in uncertainties, a case study of a realistic calculation, and Wielandt acceleration techniques. The remaining lectures cover advanced topics, including HTGR modeling and stochastic geometry, temperature dependence, fission energy deposition, depletion calculations, parallel calculations, and parameter studies. This portion of the class focuses on using MCNP to perform criticality calculations for reactor physics and criticality safety applications. It is an intermediate level class, intended for those with at least some familiarity with MCNP. Class examples provide hands-on experience at running the code, plotting both geometry and results, and understanding the code output. The class includes lectures & hands-on computer use for a variety of Monte Carlo calculations. Beginning MCNP users are encouraged to review LA-UR-09-00380, "Criticality Calculations with MCNP: A Primer (3nd Edition)" (available at http:// mcnp.lanl.gov under "Reference Collection") prior to the class. No Monte Carlo class can be complete without having students write their own simple Monte Carlo routines for basic random sampling, use of the random number generator, and simplified particle transport simulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗